Playing and Cheating in Ambient Entertainment

Nijholt, Anton

doi:10.1007/978-3-540-74873-1_51

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…As for any other affective channel, touch can also be used to send fake signals of affect. Rather than this being seen as a limitation, it should be considered a possibility to recreate a gameplay situation comparable to real life gameplay, where acted expressions can be used to confuse the opponent [Nijholt 2007]. As the player learns that the game reacts to his/her affective touch behavior, this becomes a new functionality or tool to use to bring a new level of complexity to the game.…”

Section: The Use Of Affective Touch Recognition In Gamesmentioning

confidence: 99%

What Does Touch Tell Us about Emotions in Touchscreen-Based Gameplay?

Gao

Bianchi-Berthouze

Meng

2012

ACM Trans. Comput.-Hum. Interact.

141

104

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The increasing number of people playing games on touch-screen mobile phones raises the question of whether touch behaviors reflect players' emotional states. This prospect would not only be a valuable evaluation indicator for game designers, but also for real-time personalization of the game experience. Psychology studies on acted touch behavior show the existence of discriminative affective profiles. In this article, finger-stroke features during gameplay on an iPod were extracted and their discriminative power analyzed. Machine learning algorithms were used to build systems for automatically discriminating between four emotional states (Excited, Relaxed, Frustrated, Bored), two levels of arousal and two levels of valence. Accuracy reached between 69% and 77% for the four emotional states, and higher results (∼89%) were obtained for discriminating between two levels of arousal and two levels of valence. We conclude by discussing the factors relevant to the generalization of the results to applications other than games.

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Section: The Use Of Affective Touch Recognition In Gamesmentioning

confidence: 99%

What Does Touch Tell Us about Emotions in Touchscreen-Based Gameplay?

Gao

Bianchi-Berthouze

Meng

2012

ACM Trans. Comput.-Hum. Interact.

141

104

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“…The identification and discrimination of emotional states from EEG is considered notoriously challenging, mainly due to the difficulty to gauge electromagnetic activity elicited by cortical structures involved in processing emotional information [ 1 ], yet potentially useful for a broad range of important applications such as diagnosing and treating patients with dysfunctional processing of emotional information [ 2 ], emotion-sensitive interactive games, affective interfaces, and emotion-sensitive tutoring systems [ 3 – 5 ]. This article sets out to address these challenges, but rather than evaluating the power in the standard EEG frequency bands, as is traditionally done [ 6 – 13 ], or amplitudes and latencies of event-related potentials (ERPs) in response to emotion-evoking stimuli [ 14 – 19 ], we conduct the analysis within the realm of complexity science [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Discrimination of emotional states from scalp- and intracranial EEG using multiscale Rényi entropy

Tonoyan¹,

Chanwimalueang

Mandic

et al. 2017

PLoS ONE

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A data-adaptive, multiscale version of Rényi’s quadratic entropy (RQE) is introduced for emotional state discrimination from EEG recordings. The algorithm is applied to scalp EEG recordings of 30 participants watching 4 emotionally-charged video clips taken from a validated public database. Krippendorff’s inter-rater statistic reveals that multiscale RQE of the mid-frontal scalp electrodes best discriminates between five emotional states. Multiscale RQE is also applied to joint scalp EEG, amygdala- and occipital pole intracranial recordings of an implanted patient watching a neutral and an emotionally charged video clip. Unlike for the neutral video clip, the RQEs of the mid-frontal scalp electrodes and the amygdala-implanted electrodes are observed to coincide in the time range where the crux of the emotionally-charged video clip is revealed. In addition, also during this time range, phase synchrony between the amygdala and mid-frontal recordings is maximal, as well as our 30 participants’ inter-rater agreement on the same video clip. A source reconstruction exercise using intracranial recordings supports our assertion that amygdala could contribute to mid-frontal scalp EEG. On the contrary, no such contribution was observed for the occipital pole’s intracranial recordings. Our results suggest that emotional states discriminated from mid-frontal scalp EEG are likely to be mirrored by differences in amygdala activations in particular when recorded in response to emotionally-charged scenes.

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“…Sensing user's activity in ambient entertainment environments is discussed in [36]. Rather than using questionnaires we discuss how in the near future information obtained with computer vision and other sensors can help a movement-based interface to consider experience related issues such as personality, mood, and also pain, fatigue, frustration, irritation, etc.…”

Section: More Advanced Sensing Of User and Activitiesmentioning

confidence: 99%

Observations on Experience and Flow in Movement-Based Interaction

Nijholt

Pasch

Dijk

et al. 2011

Whole Body Interaction

Self Cite

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Movement-based interfaces assume that their users move. Users have to perform exercises, they have to dance, they have to golf or football, or they want to train particular bodily skills. Many examples of those interfaces exist, sometimes asking for subtle interaction between user and interface and sometimes asking for 'brute force' interaction between user and interface. Often these interfaces mediate between players of a game. Obviously, one of the players may be a virtual human. We embed this interface research in ambient intelligence and entertainment computing research, and the interfaces we consider are not only mediating, but they also 'add' intelligence to the interaction. Intelligent movement-based interfaces, being able to know and learn about their users, should also be able to provide means to keep their users engaged in the interaction. Issues that will be discussed in this chapter are 'flow' and 'immersion' for movement-based interfaces and we look at the possible role of interaction synchrony to measure and support engagement.

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Playing and Cheating in Ambient Entertainment

Abstract: Abstract. We survey ways to extract information from users interacting in ambient intelligence entertainment environments. We speculate on the use of this information, including information obtained from physiological processes and brain-computer interfacing, in future game environments.

Cited by 5 publications

References 13 publications

What Does Touch Tell Us about Emotions in Touchscreen-Based Gameplay?

What Does Touch Tell Us about Emotions in Touchscreen-Based Gameplay?

Discrimination of emotional states from scalp- and intracranial EEG using multiscale Rényi entropy

Observations on Experience and Flow in Movement-Based Interaction

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